AI RESEARCH
NRGPT: An Energy-based Alternative for GPT
arXiv CS.LG
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ArXi:2512.16762v3 Announce Type: replace Generative Pre-trained Transformer (GPT) architectures are the most popular design for language modeling. Energy-based modeling is a different paradigm that views inference as a dynamical process operating on an energy landscape. We propose a minimal modification of the GPT setting to unify it with the EBM framework. The inference step of our model, which we call eNeRgy-GPT (NRGPT), is conceptualized as an exploration of the tokens on the energy landscape.